0guogcfcb4q156ug2eqlg_source.mp4 Online

:Modify the configuration files located in ./experiments/dff_rfcn/cfgs . Use a standard setup like resnet_v1_101_flownet_imagenet_vid_rfcn_end2end_ohem.yaml for high-performance detection.

): The model runs a full forward pass through the feature network ( Nfeatcap N sub f e a t end-sub ) to get feature maps A lightweight FlowNet ( Nflowcap N sub f l o w end-sub ) calculates the displacement field ( Mi→kcap M sub i right arrow k end-sub ) between the current frame and the last keyframe. 0guogcfcb4q156ug2eqlg_source.mp4

For further customization of the network architecture or training on specific datasets, refer to the official GitHub documentation. :Modify the configuration files located in